Name
Abstract | ||
|---|---|---|
As the smartphone/cellphone market has exploded, the war on which smartphone platform will dominate has become fiercer than ever. In that vain, the goal of this paper is to answer two fundamental questions: What are the adoption trends for smartphones? And how can we estimate the demand for new smartphones? We answer these two questions by collecting a dataset of 3 million subscribers from a nationwide telecom operator. A key aspect of our work is that we have demographic information per user, such as income level, and age, which we correlate with phone usage patterns. Interestingly, we find that in all demographic groups, Android is leading platform top in all age groups and income levels. A key question is whether the "social influence" affects the choice of phone, which we find more pronounced in business plans. Finally, we develop a predictor to infer the phone a user will switch to considering: (a) the type of previous phone, (b) the social influence, and (c) the demographics of the user. Compared with the reference method, our predictor is effective in: (a) reducing the prediction error in number of phones by 1/3, and (b) in the case of minimizing phone costs, the monetary cost by half. Apart from its interest in observations, our work could help telecom operator forecast their inventory more accurately by pointing to the right properties to consider. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/NOMS.2014.6838293 | NOMS |
Keywords | Field | DocType |
probability,correlation,market research,demand forecasting,prediction error,social influence,android,switches | Mean squared prediction error,Android (operating system),Telecommunications,Age groups,Advertising,Computer science,Computer network,Phone,Social influence,Demographics,Market research | Conference |
ISSN | Citations | PageRank |
1542-1201 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yi Wang | 1 | 114 | 9.03 |
| Hui Zang | 2 | 1052 | 77.25 |
| Pravallika Devineni | 3 | 13 | 3.61 |
| Michalis Faloutsos | 4 | 5288 | 586.88 |
| Krishna Janakiraman | 5 | 0 | 0.34 |
| Sara Motahari | 6 | 40 | 4.46 |